Physiological Aberrations in Panic Disorder Wenzel Schicho and Oliver Pogarell
Abstract Panic disorder is a frequent and clinically relevant medical entity with a high lifetime prevalence and significant impact on psychosocial stability and function. Regarding the clinical presentation, there are obvious similarities in paroxysmal neurological disorders such as seizures and focal epilepsies. In this context, the detection of EEG abnormalities during the attacks or in asymptomatic intervals, continuously or rhythmical, is of significant interest. Likewise, isolated epileptic discharges (IEDs) are important components of epilepsy. On the other hand, IEDs are also common in non-epileptic psychiatric patients. It is not known exactly which role IEDs play in the genesis of behavioural aberrations. In this chapter, attention is directed towards this issue and its relevance to managing psychiatric patients suffering from panic disorder (PD), as well as understanding the complex relationship between IEDs and the pathophysiology of PD. Two main conclusions are being proposed. First, patients suffering from PD may show a higher rate of unspecific EEG abnormalities and increased beta power, pointing to a state of hyperarousal. Secondly, if first-line treatment of PD fails, the use of antiepileptic drugs (AEDs) should be considered. There is enough evidence to suggest that IEDs play a significant role in the genesis of PD and that this relationship is far from clear, warranting more research in this field. This article gives an overview of the current literature on the pathophysiology of PD, including studies on altered microstates, coherence imaging and alpha asymmetry.
Keywords Electroencephalography Epilepsy Isolated epileptic discharge (IED) Psychopathology Panic disorder Seizure disorder Synchronicity
W. Schicho (&) O. Pogarell Department of Psychiatry and Psychotherapy, University of Munich, Nussbaumstr. 7, 80336 Munich, Germany e-mail: [email protected] © Springer-Verlag Berlin Heidelberg 2014 Curr Topics Behav Neurosci DOI 10.1007/7854_2014_347
W. Schicho and O. Pogarell
Contents 1 Introduction .............................................................................................................................. 2 Electrophysiology Studies in Anxiety Disorders and Panic Disorder: EEG.......................... 3 Resting State EEG: Microstates and Alpha Asymmetry ........................................................ 4 qEEG, MEG and Coherence Analysis .................................................................................... 5 Panic Disorder and Epilepsy ................................................................................................... 6 Theoretical Consideration ........................................................................................................ 7 Conclusion ............................................................................................................................... References ......................................................................................................................................
1 Introduction With a lifetime prevalence of about 3–4 % (Jacobi et al. 2004), panic disorder (PD) is a rather common medical entity (Hirschfeld 1996; Asnaani et al. 2010; Skapinakis et al. 2011). Episodes of intense fear occurring more than once a week for at least one month are the key feature of PD, but also feelings of derealisation or depersonalisation and miscellaneous autonomic symptoms such as palpitations, nausea, sweating or chest pain are associated with PD (Ham et al. 2005; Hurley et al. 2006). Panic attacks (PA) can result in agoraphobia with severe psychosocial and economic consequences (Boutros et al. 2013a, b). In the clinical routine, it can be difficult to distinguish PA from anxiety attacks in the context of epileptic fits, since there is a significant overlap of these two entities concerning their diagnostic criteria according to DSM-V and ICD-10 (Mintzer and Lopez 2002; Beyenburg et al. 2005). Especially, patients diagnosed with partial seizures originating from temporal structures are likely to present symptoms resembling those of a PD (Adamaszek et al. 2011). Because the limbic system comprises important neural networks involved in the processing of fear and related emotions, it is likely that abnormal synchronous activity induced by epileptic seizures in this area leads to symptoms which are indicative of PA (Hurley et al. 2006; Ray et al. 2007). Patients with seizures or epilepsy suffering solely from so-called ictal fear accompanied by autonomic symptoms can easily be misdiagnosed with PD (Wieser 1983; Young et al. 1995; Sazgar et al. 2003). Kanner (2011) provided a detailed overview of how to clinically distinguish ictal panic, PA and postictal panic. However, he states that apart from clinical observations, EEG, neuroimaging and the assessment of prolactin levels can be of additional help in the diagnostic process (Kanner 2011).
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2 Electrophysiology Studies in Anxiety Disorders and Panic Disorder: EEG Regarding the differential diagnosis PD versus epilepsy, there have been reports on several patients with a PD, showing characteristics of abnormal synchronous cerebral activity or even epileptiform discharges in scalp EEG, but no other traces of an underlying epileptic entity (Jabourian et al. 1992; Gallinat et al. 2003; Avoli et al. 2005). Up to now, clinicians tend to think in a dichotomous way whether a panic attack is of psychiatric origin or a seizure disorder. But there are cases where even extensive workup fails to resolve this dichotomy. It is being discussed that the underlying pathology of PA could be abnormal hyperexcitability which fails to generate potentials large enough to be detected on the scalp (Boutros et al. 2013a, b). Given the relatively high false-negative rate of scalp EEG in detecting epileptic discharges (Boutros 2010), it should be considered that what we see in the standard scalp EEG is only the ‘tip of an iceberg’ (Boutros et al. 2013a, b). Weilburg et al. (1993) reported on two patients with atypical PA while their EEGs were being monitored. Focal paroxysms of sharp wave activity appeared in the EEG coinciding with a spontaneous onset of panic attack symptoms in both patients (Weilburg et al. 1993). Consciousness was maintained during these episodes. Later, the same group reported on 15 subjects with atypical PA who met DSM-IIIR criteria for PD and who underwent a routine EEG followed by prolonged ambulatory EEG monitoring using sphenoidal electrodes (Weilburg et al. 1995). They found focal paroxysmal EEG changes consistent with partial seizure activity, which had occurred during PA in 33 % (N = 5) of the subjects. It is important to note that multiple attacks were recorded before panic-related EEG changes were demonstrated. Moreover, two of the five subjects with demonstrated EEG abnormalities during PA had perfectly normal baseline EEGs. Weilburg et al. concluded that it would be necessary to monitor the EEG during multiple attacks in order to reveal an association between atypical PA and epileptiform EEG changes. This conclusion is in agreement with a report from Jabourian et al. (1992). They performed 24-h ambulatory EEGs in a population of 300 non-epileptic outpatients with an anxious and depressive pathology and subjects with PA. The recordings revealed a high prevalence of abnormalities in subjects diagnosed with PD. Two groups of 150 medication-free patients each had been selected on the base of DSM-IIIR, one with PA and the other with depressive patients without paroxysmal anxiety (DS). The results showed 62.3 % abnormal records in the PA group, while in the DS group, 74.5 % of the records were normal. Epileptiform abnormalities were four times more frequent in the PA group (80 %) than in the DS group (20 %). MRI allowed the discovery of abnormal cerebral images in 3 patients of the PA group (cyst of the insula, temporal and parietal cryptic angiomas, sequelae of a parietal vasculo-cerebral stroke) (Jabourian et al. 1992). Gallinat and Hegerl (1999) reported on a patient presenting with anxiety and clear PA who intermittently showed bitemporal spikes and spike wave complexes in scalp EEG recordings. The treatment with valproic acid led to a normalisation of the EEG and a remission of
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psychopathology. They reviewed similar cases in the literature and concluded that at least in a subgroup of patients with PA and PD, their psychopathology could be related to epileptiform activity within the limbic system, but that the confirmation of this association was difficult, since discharges of the limbic system in the depth of the brain often cannot be detected in scalp EEG recordings. Nevertheless, therapeutic trials with antiepileptic drugs (AEDs) such as valproate seemed to be a reasonable approach (Gallinat and Hegerl 1999). Vaaler et al. (2009) extended the research field from PD to a condition they called acute unstable depressive syndrome (AUDS). They compared EEGs and MRIs of 16 patients diagnosed with AUDS to 16 controls diagnosed with major depressive episodes according to DSM-IV. They also found that short-lasting atypical depressive symptoms seemed to be associated with a high frequency of epileptic and pathologic EEG activity (Vaaler et al. 2009).
3 Resting State EEG: Microstates and Alpha Asymmetry A normal stimulus processed in a pathological way can lead to PA in patients suffering from PD. By analysing resting state EEGs from both PD patients and healthy controls, it could be elucidated how pre-activated fear-associated networks were involved in this aberrant processing of normal stimuli. Kikuchi et al. (2011) analysed resting state EEGs of 18 drug-naive patients and 18 healthy controls using features of transiently stable brain states, so-called microstates, which correlate significantly with resting state networks assessed by fMRI (Britz et al. 2010; Van de Ville et al. 2010; Kikuchi et al. 2011). It could be observed that some microstate classes differ between healthy controls and PD patients, indicating that some brain functions are already altered during resting state, which may lead to a dysfunctional processing of phobic stimuli (Kikuchi et al. 2011). Gordon et al. (2010) assessed resting brain laterality in six clinical disorders in order to obtain a more fine-grained image of the utility of alpha asymmetry as a diagnostic and treatment predictive marker. Their results showed that alpha asymmetry may be of more clinical utility as a biomarker for schizophrenia and depression but less so for PD, since the PD group did not show any significant deviance in alpha asymmetry compared to the healthy control group (Gordon et al. 2010).
4 qEEG, MEG and Coherence Analysis Clark et al. (2009) provided a systematic, evidence-based review of the field of electrophysiology in anxiety disorders, characterising the clinical value of EEG and quantitative EEG (qEEG) in the diagnostic process (Clark et al. 2009). It was summarised that qEEG studies in PD indicate symptom-based abnormalities on
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basal levels of cortical arousal during waking. In patients not presenting with symptoms of depersonalisation and/or derealisation resting cortical hyperarousal with decreased power in lower frequencies and increased power in the beta range could be detected, while in patients with the aforementioned symptoms, lower frequency power was increased. This could point to a hyperarousal basal state (Clark et al. 2009). Furthermore, it was stated that in patients with PD, habituation seems to be altered, which had already been shown in studies analysing eventrelated potentials (ERP). It was also mentioned that these alterations could be associated with brainstem pathology and with subsequent early processing of sensory stimuli (Clark et al. 2009). Engelbregt et al. (2012) reported on a patient suffering from specific phobia similar to agoraphobia with PD. Panic was specifically triggered by leaving the patients domicile, so an EEG was obtained while the patient was provoking the initiation of a panic attack by driving a car out of his hometown. Similar to the aforementioned findings, the EEG showed an increase of frontal beta activity and decrease in frontal–central theta activity during the panic attack (Engelbregt 2012). It is hypothesised that panic could induce changes in functional connectivity patterns in several brain areas including frontal brain, temporal and parietal cortex and subcortical regions, referring to an earlier resting state fMRI study (Dieler et al. 2008; Engelbregt 2012). Coburn et al. (2006) stated that the qEEG literature on anxiety disorders is small and unimpressive regarding clinical utility, but they also suggested that qEEG may become an important research tool and in the future an important clinical tool (Coburn et al. 2006). Boutros et al. (2013a, b) reported on a 33-year-old patient with PA and autonomic symptoms such as stomach pain and fainting. The treatment with bupropion, alprazolam, paroxetine and clonazepam did not decrease the PAs; on the contrary, the two latter substances even worsened the patient’s complaints. No EEG correlates could be found during the PA. Extensive workup, including qEEG utilising low-resolution electromagnetic tomographie (LORETA), a PET-Scan and magnetencephalography (MEG), pointed to multiple loci of cerebral involvement suggesting the presence of an epileptic process (Boutros et al. 2013a, b). MEG is said to be more sensitive in detecting epileptic discharges in comparison with EEG (Lewine et al. 1999; Lin et al. 2003) and allows the detection of extremely high coherence values in various brain regions in close proximity to each other. Previous studies demonstrated that focal epileptic activity is associated with increased coherence between pathologically altered and other brain regions (Towle et al. 1999; Elisevich et al. 2011). Considering that these findings indicate that in this case of PD there could be an underlying subclinical epileptic process, gabapentin was added to the regimen and led to a decrease in the number of PA (Boutros et al. 2013a, b). In another study, Boutros et al. (2013a, b) investigated the presence of increased coherence in the limbic frontotemporal regions in patients suffering from PD and was indeed able to show that coherence imaging values were significantly higher in PD patients than in healthy controls (Boutros et al. 2013a, b). These findings could
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be of importance in choosing the right treatment for the population of patients with PD and increased coherence values, assuming that they would favourably respond to benzodiazepines or AEDs. This is of special importance considering the fact that the treatment strategies available today for PD are only successful in approximately half of the affected subjects (Doyle and Pollack 2004).
5 Panic Disorder and Epilepsy Toni et al. (1996) compared symptoms of PA to those of temporal lobe complex partial seizures showing a significant overlap (Toni et al. 1996). The study claims to be the first to focus on psychosensorial and related phenomena in PD with agoraphobia and derealisation/depersonalisation (PDA-DD) in comparison with complex partial epilepsy with depersonalisation/derealisation (CPE-DD). The findings show that most features of DD are present in both groups with no significant difference, with the exception for the feeling that one’s limbs are unreal (significantly higher in the PDA-DD group) and space or temporal disorientation (significantly higher in the CPE-DD group). It is also stated that hallucination was the main feature to fully discriminate PDA from CPE patients, as hallucinations were not traced in PDA patients (Toni et al. 1996). In conclusion, already in this article it is said that the broad overlap of symptoms of CPE and PDA makes a common neurophysiological substrate of both entities likely, but it has yet to be defined. Deutsch et al. (2009) reported on a 34-year-old woman with a long history of anxiety attacks together with depersonalisation, derealisation and internal derogatory voices, frightening imagery and suicidal ideation. EEG and MRI results were found to be normal, but temporal lobe epilepsy (TLE) was considered to be a differential diagnosis because the patient did not respond to the first-line treatment of PD. Similar to the aforementioned cases, the patient responded rapidly and dramatically to carbamazepine (Deutsch et al. 2009). Gerez et al. (2011) reported on two cases diagnosed with PD, who partially responded to first-line treatment such as SSRIs and psychotherapy. After having a panic attack with minimal EEG alterations, both cases developed a clear ictal EEG pattern associated with strong fear content. LORETA analysis revealed increased activity in the right amygdala during panic symptoms, demonstrating the major role of amygdalar hyperactivity in both fear-related conditions (Gerez et al. 2011) and underlining the long debated relationship of PD and TLE (Alvarez-Silva et al. 2006). Again, the most conclusive evidence came from treatment response as both patients were panic-free under carbamazepine. Two possible anatomical locations seem to be strongly involved in the generation of panic symptoms: • The amygdala is an almond-sized (about 1-inch long) brain structure which has long been linked to the experience of fear and emotional states in general. Electrical stimulation of the medial temporal structures, and more specifically
Physiological Aberrations in Panic Disorder
the amygdala, predictably induces experiential feelings and mainly fear (Gloor et al. 1982). Amygdala source panic is likely to be characterised by a dominance of fear, with other autonomic symptoms following either secondary to the development of epileptic activity or as a psychological reaction to fear (Kalynchuk 2000; Keele 2005). The two cases reported by Gerez et al. (2011) demonstrated the close link between seizures originating from the mesial temporal structures and panic symptoms, with amygdala hyperactivity underlying both phenomena (Gerez et al. 2011). When the amygdala is electrically stimulated in awake humans (usually during epilepsy workup or surgery), fear is the most commonly generated experience (Meletti et al. 2006). The stimulation of even close structures such as the hippocampus (with avoiding an amygdala involvement) leads to far fewer fear reactions. This group also pointed to a gender difference in the reaction to the electrical stimulation of the amygdala, with women more likely to experience fear (Meletti et al. 2006). In addition, the stimulation of both amygdalas (right and left) leads to different responses. The electrical stimulation of the right amygdala induced negative symptoms, especially fear and sadness, while the stimulation of the left amygdala induced either pleasant (e.g. happiness) or unpleasant (e.g. fear, anxiety, sadness) sensations (Lanteaume et al. 2007). • The insula is located deep within the Sylvian fissure beneath the frontal, parietal and temporal opercula. The insula has been long associated with visceral functions and is responsible for integrating autonomic information. The insula has wide connections with the neocortex, basal ganglia, thalamus and the amygdala among other limbic structures. This wide connectivity explains the varied symptoms of seizures originating from this region (Nguyen et al. 2009). It is important to highlight that epileptic activity emanating from this small and deep region is unlikely to be detected by standard scalp EEG. Insular temporal cortex source PA begin with autonomic symptoms and fear following either secondary spread of epileptic activity or a conditioned response to the experience of sudden and usually unprovoked autonomic activation (Nguyen et al. 2009).
6 Theoretical Consideration Whether IEDs can be associated with actual clinical manifestations such as fear or autonomic responses is unknown, but it is a very important question for a number of reasons. Firstly, an IED lasts only a fraction of a second, whereas a typical panic attack can last several minutes. The current requirements to diagnose a panic attack as an actual seizure are difficult to meet. The American Academy of Neurology requires that for any behaviour to be labelled a seizure, evidence for ongoing ictal activity during the behaviour must be documented on a simultaneous EEG/video monitoring. If a single or a short run of IEDs can indeed induce or spark a panic
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attack, more research is needed to understand how a very short-duration event can induce a (usually) much longer experience. In fact, the relationship between the presence of epileptic discharges in the amygdala or insular regions and the emergence of panic symptoms is likely to be much more complex than the simple notion of an electric stimulus activating the function of a particular brain region. This is exemplified by the reports of Mintzer and Lopez (2002) showing panic symptoms getting worse after epileptic lesions were surgically removed (Mintzer and Lopez 2002). Some evidence is beginning to accumulate that abnormal discharges may be causing disturbances in the workings of the fear neural circuitry (Bartolomei et al. 2005). The group provided evidence that during ictal activity associated with intense emotional alterations, a significant decrease in synchrony between signals recorded from the neural networks known to be involved in emotional processing was present. In particular, loss of synchrony between the orbitofrontal cortex and the amygdala was noted (Bartolomei et al. 2005). The authors suggested that the disconnection releases the amygdala from the inhibitory control of the frontal lobe, allowing usually suppressed fear to emerge. Furthermore, Kellett and Kokkinidis (2004) suggested conditioning the epileptic discharges to fear experiences to be a prerequisite for the development of panic symptoms. They showed that animals failed to demonstrate fear-potentiated startle responses when electrical stimulation of the amygdala was unconditioned (Kellett and Kokkinidis 2004). This would explain why not all individuals with epileptic spikes in this location develop PA. The proper neurochemical state for developing conditioned fear may also be a prerequisite. The dopamine-containing ventral tegmental area (VTA) is known to be activated by threatening environmental stimuli and has been shown to be an important variable related to neural excitability of the amygdala (Gelowitz and Kokkinidis 1999).
7 Conclusion According to the EEG literature, patients with PD or PA present with a higher rate of unspecific EEG abnormalities, including paroxysmal EEG changes or epileptic discharges. QEEG studies showed differences between groups of PD patients and healthy controls related to the fear-associated networks, and PD patients may show increased beta power which could be in line with a state of hyperarousal. Regarding the association of PD and epilepsy, there are reports that ictal EEG patterns and epileptic discharges can be associated with symptoms of fear and panic. Thus, if pharmacological treatment approaches with SSRI, TCA, MAO inhibitors and psychotherapy do not lead to a clinical amelioration in patients suffering from PD, the use of AEDs, especially carbamazepine and valproic acid, should be considered (Adamaszek et al. 2011). Boutros et al. (2014) recently gave a comprehensive review of the current literature on the predictive value of IEDs for a favourable therapeutic response to AEDs in non-epileptic patients (Boutros et al. 2014). They found that the number of controlled studies in this field was extremely small and the
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majority of citations found were single case reports or case series. Another problem is that the clinical significance of IEDs is mainly discussed in neurology (Gorji and Speckmann 2009), but often unrecognised and rarely studied in psychiatry (Boutros 2009). Therefore, clinicians caring for psychiatric patients need to develop the necessary skills to be able to interpret results from advancing neurodiagnostic technologies (Boutros et al. 2013a, b). Psychiatric clinicians need to be more familiar with electroencephalography, its advantages as well as its limitations. More research is needed in this field to better define indications, adequate EEG workups, best AEDs to be used and optimal durations of treatment (Boutros et al. 2014). Multimodal EEG approaches, including resting and long-term recordings, and simultaneous video-EEG-recordings should be considered during the diagnostic workup of PD patients (Adamaszek et al. 2011). With recent developments in the investigation of altered synchronous neuronal activities (such as the combination of EEG/fMRI or MEG and coherence or microstate analysis), there are a couple of promising techniques emerging which may be helpful to better understand the underlying neurophysiologic mechanisms of PD in the future (Ray et al. 2007; Jacobs et al. 2009; Adamaszek et al. 2011).
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Abstract Panic disorder is a frequent and clinically relevant medical entity with a high lifetime prevalence and significant impact on psychosocial stability and function. Regarding the clinical presentation, there are obvious similarities in paroxysmal neurological disorders such as seizures and focal epilepsies. In this context, the detection of EEG abnormalities during the attacks or in asymptomatic intervals, continuously or rhythmical, is of significant interest. Likewise, isolated epileptic discharges (IEDs) are important components of epilepsy. On the other hand, IEDs are also common in non-epileptic psychiatric patients. It is not known exactly which role IEDs play in the genesis of behavioural aberrations. In this chapter, attention is directed towards this issue and its relevance to managing psychiatric patients suffering from panic disorder (PD), as well as understanding the complex relationship between IEDs and the pathophysiology of PD. Two main conclusions are being proposed. First, patients suffering from PD may show a higher rate of unspecific EEG abnormalities and increased beta power, pointing to a state of hyperarousal. Secondly, if first-line treatment of PD fails, the use of antiepileptic drugs (AEDs) should be considered. There is enough evidence to suggest that IEDs play a significant role in the genesis of PD and that this relationship is far from clear, warranting more research in this field. This article gives an overview of the current literature on the pathophysiology of PD, including studies on altered microstates, coherence imaging and alpha asymmetry.
Keywords Electroencephalography Epilepsy Isolated epileptic discharge (IED) Psychopathology Panic disorder Seizure disorder Synchronicity
W. Schicho (&) O. Pogarell Department of Psychiatry and Psychotherapy, University of Munich, Nussbaumstr. 7, 80336 Munich, Germany e-mail: [email protected] © Springer-Verlag Berlin Heidelberg 2014 Curr Topics Behav Neurosci DOI 10.1007/7854_2014_347
W. Schicho and O. Pogarell
Contents 1 Introduction .............................................................................................................................. 2 Electrophysiology Studies in Anxiety Disorders and Panic Disorder: EEG.......................... 3 Resting State EEG: Microstates and Alpha Asymmetry ........................................................ 4 qEEG, MEG and Coherence Analysis .................................................................................... 5 Panic Disorder and Epilepsy ................................................................................................... 6 Theoretical Consideration ........................................................................................................ 7 Conclusion ............................................................................................................................... References ......................................................................................................................................
1 Introduction With a lifetime prevalence of about 3–4 % (Jacobi et al. 2004), panic disorder (PD) is a rather common medical entity (Hirschfeld 1996; Asnaani et al. 2010; Skapinakis et al. 2011). Episodes of intense fear occurring more than once a week for at least one month are the key feature of PD, but also feelings of derealisation or depersonalisation and miscellaneous autonomic symptoms such as palpitations, nausea, sweating or chest pain are associated with PD (Ham et al. 2005; Hurley et al. 2006). Panic attacks (PA) can result in agoraphobia with severe psychosocial and economic consequences (Boutros et al. 2013a, b). In the clinical routine, it can be difficult to distinguish PA from anxiety attacks in the context of epileptic fits, since there is a significant overlap of these two entities concerning their diagnostic criteria according to DSM-V and ICD-10 (Mintzer and Lopez 2002; Beyenburg et al. 2005). Especially, patients diagnosed with partial seizures originating from temporal structures are likely to present symptoms resembling those of a PD (Adamaszek et al. 2011). Because the limbic system comprises important neural networks involved in the processing of fear and related emotions, it is likely that abnormal synchronous activity induced by epileptic seizures in this area leads to symptoms which are indicative of PA (Hurley et al. 2006; Ray et al. 2007). Patients with seizures or epilepsy suffering solely from so-called ictal fear accompanied by autonomic symptoms can easily be misdiagnosed with PD (Wieser 1983; Young et al. 1995; Sazgar et al. 2003). Kanner (2011) provided a detailed overview of how to clinically distinguish ictal panic, PA and postictal panic. However, he states that apart from clinical observations, EEG, neuroimaging and the assessment of prolactin levels can be of additional help in the diagnostic process (Kanner 2011).
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2 Electrophysiology Studies in Anxiety Disorders and Panic Disorder: EEG Regarding the differential diagnosis PD versus epilepsy, there have been reports on several patients with a PD, showing characteristics of abnormal synchronous cerebral activity or even epileptiform discharges in scalp EEG, but no other traces of an underlying epileptic entity (Jabourian et al. 1992; Gallinat et al. 2003; Avoli et al. 2005). Up to now, clinicians tend to think in a dichotomous way whether a panic attack is of psychiatric origin or a seizure disorder. But there are cases where even extensive workup fails to resolve this dichotomy. It is being discussed that the underlying pathology of PA could be abnormal hyperexcitability which fails to generate potentials large enough to be detected on the scalp (Boutros et al. 2013a, b). Given the relatively high false-negative rate of scalp EEG in detecting epileptic discharges (Boutros 2010), it should be considered that what we see in the standard scalp EEG is only the ‘tip of an iceberg’ (Boutros et al. 2013a, b). Weilburg et al. (1993) reported on two patients with atypical PA while their EEGs were being monitored. Focal paroxysms of sharp wave activity appeared in the EEG coinciding with a spontaneous onset of panic attack symptoms in both patients (Weilburg et al. 1993). Consciousness was maintained during these episodes. Later, the same group reported on 15 subjects with atypical PA who met DSM-IIIR criteria for PD and who underwent a routine EEG followed by prolonged ambulatory EEG monitoring using sphenoidal electrodes (Weilburg et al. 1995). They found focal paroxysmal EEG changes consistent with partial seizure activity, which had occurred during PA in 33 % (N = 5) of the subjects. It is important to note that multiple attacks were recorded before panic-related EEG changes were demonstrated. Moreover, two of the five subjects with demonstrated EEG abnormalities during PA had perfectly normal baseline EEGs. Weilburg et al. concluded that it would be necessary to monitor the EEG during multiple attacks in order to reveal an association between atypical PA and epileptiform EEG changes. This conclusion is in agreement with a report from Jabourian et al. (1992). They performed 24-h ambulatory EEGs in a population of 300 non-epileptic outpatients with an anxious and depressive pathology and subjects with PA. The recordings revealed a high prevalence of abnormalities in subjects diagnosed with PD. Two groups of 150 medication-free patients each had been selected on the base of DSM-IIIR, one with PA and the other with depressive patients without paroxysmal anxiety (DS). The results showed 62.3 % abnormal records in the PA group, while in the DS group, 74.5 % of the records were normal. Epileptiform abnormalities were four times more frequent in the PA group (80 %) than in the DS group (20 %). MRI allowed the discovery of abnormal cerebral images in 3 patients of the PA group (cyst of the insula, temporal and parietal cryptic angiomas, sequelae of a parietal vasculo-cerebral stroke) (Jabourian et al. 1992). Gallinat and Hegerl (1999) reported on a patient presenting with anxiety and clear PA who intermittently showed bitemporal spikes and spike wave complexes in scalp EEG recordings. The treatment with valproic acid led to a normalisation of the EEG and a remission of
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psychopathology. They reviewed similar cases in the literature and concluded that at least in a subgroup of patients with PA and PD, their psychopathology could be related to epileptiform activity within the limbic system, but that the confirmation of this association was difficult, since discharges of the limbic system in the depth of the brain often cannot be detected in scalp EEG recordings. Nevertheless, therapeutic trials with antiepileptic drugs (AEDs) such as valproate seemed to be a reasonable approach (Gallinat and Hegerl 1999). Vaaler et al. (2009) extended the research field from PD to a condition they called acute unstable depressive syndrome (AUDS). They compared EEGs and MRIs of 16 patients diagnosed with AUDS to 16 controls diagnosed with major depressive episodes according to DSM-IV. They also found that short-lasting atypical depressive symptoms seemed to be associated with a high frequency of epileptic and pathologic EEG activity (Vaaler et al. 2009).
3 Resting State EEG: Microstates and Alpha Asymmetry A normal stimulus processed in a pathological way can lead to PA in patients suffering from PD. By analysing resting state EEGs from both PD patients and healthy controls, it could be elucidated how pre-activated fear-associated networks were involved in this aberrant processing of normal stimuli. Kikuchi et al. (2011) analysed resting state EEGs of 18 drug-naive patients and 18 healthy controls using features of transiently stable brain states, so-called microstates, which correlate significantly with resting state networks assessed by fMRI (Britz et al. 2010; Van de Ville et al. 2010; Kikuchi et al. 2011). It could be observed that some microstate classes differ between healthy controls and PD patients, indicating that some brain functions are already altered during resting state, which may lead to a dysfunctional processing of phobic stimuli (Kikuchi et al. 2011). Gordon et al. (2010) assessed resting brain laterality in six clinical disorders in order to obtain a more fine-grained image of the utility of alpha asymmetry as a diagnostic and treatment predictive marker. Their results showed that alpha asymmetry may be of more clinical utility as a biomarker for schizophrenia and depression but less so for PD, since the PD group did not show any significant deviance in alpha asymmetry compared to the healthy control group (Gordon et al. 2010).
4 qEEG, MEG and Coherence Analysis Clark et al. (2009) provided a systematic, evidence-based review of the field of electrophysiology in anxiety disorders, characterising the clinical value of EEG and quantitative EEG (qEEG) in the diagnostic process (Clark et al. 2009). It was summarised that qEEG studies in PD indicate symptom-based abnormalities on
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basal levels of cortical arousal during waking. In patients not presenting with symptoms of depersonalisation and/or derealisation resting cortical hyperarousal with decreased power in lower frequencies and increased power in the beta range could be detected, while in patients with the aforementioned symptoms, lower frequency power was increased. This could point to a hyperarousal basal state (Clark et al. 2009). Furthermore, it was stated that in patients with PD, habituation seems to be altered, which had already been shown in studies analysing eventrelated potentials (ERP). It was also mentioned that these alterations could be associated with brainstem pathology and with subsequent early processing of sensory stimuli (Clark et al. 2009). Engelbregt et al. (2012) reported on a patient suffering from specific phobia similar to agoraphobia with PD. Panic was specifically triggered by leaving the patients domicile, so an EEG was obtained while the patient was provoking the initiation of a panic attack by driving a car out of his hometown. Similar to the aforementioned findings, the EEG showed an increase of frontal beta activity and decrease in frontal–central theta activity during the panic attack (Engelbregt 2012). It is hypothesised that panic could induce changes in functional connectivity patterns in several brain areas including frontal brain, temporal and parietal cortex and subcortical regions, referring to an earlier resting state fMRI study (Dieler et al. 2008; Engelbregt 2012). Coburn et al. (2006) stated that the qEEG literature on anxiety disorders is small and unimpressive regarding clinical utility, but they also suggested that qEEG may become an important research tool and in the future an important clinical tool (Coburn et al. 2006). Boutros et al. (2013a, b) reported on a 33-year-old patient with PA and autonomic symptoms such as stomach pain and fainting. The treatment with bupropion, alprazolam, paroxetine and clonazepam did not decrease the PAs; on the contrary, the two latter substances even worsened the patient’s complaints. No EEG correlates could be found during the PA. Extensive workup, including qEEG utilising low-resolution electromagnetic tomographie (LORETA), a PET-Scan and magnetencephalography (MEG), pointed to multiple loci of cerebral involvement suggesting the presence of an epileptic process (Boutros et al. 2013a, b). MEG is said to be more sensitive in detecting epileptic discharges in comparison with EEG (Lewine et al. 1999; Lin et al. 2003) and allows the detection of extremely high coherence values in various brain regions in close proximity to each other. Previous studies demonstrated that focal epileptic activity is associated with increased coherence between pathologically altered and other brain regions (Towle et al. 1999; Elisevich et al. 2011). Considering that these findings indicate that in this case of PD there could be an underlying subclinical epileptic process, gabapentin was added to the regimen and led to a decrease in the number of PA (Boutros et al. 2013a, b). In another study, Boutros et al. (2013a, b) investigated the presence of increased coherence in the limbic frontotemporal regions in patients suffering from PD and was indeed able to show that coherence imaging values were significantly higher in PD patients than in healthy controls (Boutros et al. 2013a, b). These findings could
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be of importance in choosing the right treatment for the population of patients with PD and increased coherence values, assuming that they would favourably respond to benzodiazepines or AEDs. This is of special importance considering the fact that the treatment strategies available today for PD are only successful in approximately half of the affected subjects (Doyle and Pollack 2004).
5 Panic Disorder and Epilepsy Toni et al. (1996) compared symptoms of PA to those of temporal lobe complex partial seizures showing a significant overlap (Toni et al. 1996). The study claims to be the first to focus on psychosensorial and related phenomena in PD with agoraphobia and derealisation/depersonalisation (PDA-DD) in comparison with complex partial epilepsy with depersonalisation/derealisation (CPE-DD). The findings show that most features of DD are present in both groups with no significant difference, with the exception for the feeling that one’s limbs are unreal (significantly higher in the PDA-DD group) and space or temporal disorientation (significantly higher in the CPE-DD group). It is also stated that hallucination was the main feature to fully discriminate PDA from CPE patients, as hallucinations were not traced in PDA patients (Toni et al. 1996). In conclusion, already in this article it is said that the broad overlap of symptoms of CPE and PDA makes a common neurophysiological substrate of both entities likely, but it has yet to be defined. Deutsch et al. (2009) reported on a 34-year-old woman with a long history of anxiety attacks together with depersonalisation, derealisation and internal derogatory voices, frightening imagery and suicidal ideation. EEG and MRI results were found to be normal, but temporal lobe epilepsy (TLE) was considered to be a differential diagnosis because the patient did not respond to the first-line treatment of PD. Similar to the aforementioned cases, the patient responded rapidly and dramatically to carbamazepine (Deutsch et al. 2009). Gerez et al. (2011) reported on two cases diagnosed with PD, who partially responded to first-line treatment such as SSRIs and psychotherapy. After having a panic attack with minimal EEG alterations, both cases developed a clear ictal EEG pattern associated with strong fear content. LORETA analysis revealed increased activity in the right amygdala during panic symptoms, demonstrating the major role of amygdalar hyperactivity in both fear-related conditions (Gerez et al. 2011) and underlining the long debated relationship of PD and TLE (Alvarez-Silva et al. 2006). Again, the most conclusive evidence came from treatment response as both patients were panic-free under carbamazepine. Two possible anatomical locations seem to be strongly involved in the generation of panic symptoms: • The amygdala is an almond-sized (about 1-inch long) brain structure which has long been linked to the experience of fear and emotional states in general. Electrical stimulation of the medial temporal structures, and more specifically
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the amygdala, predictably induces experiential feelings and mainly fear (Gloor et al. 1982). Amygdala source panic is likely to be characterised by a dominance of fear, with other autonomic symptoms following either secondary to the development of epileptic activity or as a psychological reaction to fear (Kalynchuk 2000; Keele 2005). The two cases reported by Gerez et al. (2011) demonstrated the close link between seizures originating from the mesial temporal structures and panic symptoms, with amygdala hyperactivity underlying both phenomena (Gerez et al. 2011). When the amygdala is electrically stimulated in awake humans (usually during epilepsy workup or surgery), fear is the most commonly generated experience (Meletti et al. 2006). The stimulation of even close structures such as the hippocampus (with avoiding an amygdala involvement) leads to far fewer fear reactions. This group also pointed to a gender difference in the reaction to the electrical stimulation of the amygdala, with women more likely to experience fear (Meletti et al. 2006). In addition, the stimulation of both amygdalas (right and left) leads to different responses. The electrical stimulation of the right amygdala induced negative symptoms, especially fear and sadness, while the stimulation of the left amygdala induced either pleasant (e.g. happiness) or unpleasant (e.g. fear, anxiety, sadness) sensations (Lanteaume et al. 2007). • The insula is located deep within the Sylvian fissure beneath the frontal, parietal and temporal opercula. The insula has been long associated with visceral functions and is responsible for integrating autonomic information. The insula has wide connections with the neocortex, basal ganglia, thalamus and the amygdala among other limbic structures. This wide connectivity explains the varied symptoms of seizures originating from this region (Nguyen et al. 2009). It is important to highlight that epileptic activity emanating from this small and deep region is unlikely to be detected by standard scalp EEG. Insular temporal cortex source PA begin with autonomic symptoms and fear following either secondary spread of epileptic activity or a conditioned response to the experience of sudden and usually unprovoked autonomic activation (Nguyen et al. 2009).
6 Theoretical Consideration Whether IEDs can be associated with actual clinical manifestations such as fear or autonomic responses is unknown, but it is a very important question for a number of reasons. Firstly, an IED lasts only a fraction of a second, whereas a typical panic attack can last several minutes. The current requirements to diagnose a panic attack as an actual seizure are difficult to meet. The American Academy of Neurology requires that for any behaviour to be labelled a seizure, evidence for ongoing ictal activity during the behaviour must be documented on a simultaneous EEG/video monitoring. If a single or a short run of IEDs can indeed induce or spark a panic
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attack, more research is needed to understand how a very short-duration event can induce a (usually) much longer experience. In fact, the relationship between the presence of epileptic discharges in the amygdala or insular regions and the emergence of panic symptoms is likely to be much more complex than the simple notion of an electric stimulus activating the function of a particular brain region. This is exemplified by the reports of Mintzer and Lopez (2002) showing panic symptoms getting worse after epileptic lesions were surgically removed (Mintzer and Lopez 2002). Some evidence is beginning to accumulate that abnormal discharges may be causing disturbances in the workings of the fear neural circuitry (Bartolomei et al. 2005). The group provided evidence that during ictal activity associated with intense emotional alterations, a significant decrease in synchrony between signals recorded from the neural networks known to be involved in emotional processing was present. In particular, loss of synchrony between the orbitofrontal cortex and the amygdala was noted (Bartolomei et al. 2005). The authors suggested that the disconnection releases the amygdala from the inhibitory control of the frontal lobe, allowing usually suppressed fear to emerge. Furthermore, Kellett and Kokkinidis (2004) suggested conditioning the epileptic discharges to fear experiences to be a prerequisite for the development of panic symptoms. They showed that animals failed to demonstrate fear-potentiated startle responses when electrical stimulation of the amygdala was unconditioned (Kellett and Kokkinidis 2004). This would explain why not all individuals with epileptic spikes in this location develop PA. The proper neurochemical state for developing conditioned fear may also be a prerequisite. The dopamine-containing ventral tegmental area (VTA) is known to be activated by threatening environmental stimuli and has been shown to be an important variable related to neural excitability of the amygdala (Gelowitz and Kokkinidis 1999).
7 Conclusion According to the EEG literature, patients with PD or PA present with a higher rate of unspecific EEG abnormalities, including paroxysmal EEG changes or epileptic discharges. QEEG studies showed differences between groups of PD patients and healthy controls related to the fear-associated networks, and PD patients may show increased beta power which could be in line with a state of hyperarousal. Regarding the association of PD and epilepsy, there are reports that ictal EEG patterns and epileptic discharges can be associated with symptoms of fear and panic. Thus, if pharmacological treatment approaches with SSRI, TCA, MAO inhibitors and psychotherapy do not lead to a clinical amelioration in patients suffering from PD, the use of AEDs, especially carbamazepine and valproic acid, should be considered (Adamaszek et al. 2011). Boutros et al. (2014) recently gave a comprehensive review of the current literature on the predictive value of IEDs for a favourable therapeutic response to AEDs in non-epileptic patients (Boutros et al. 2014). They found that the number of controlled studies in this field was extremely small and the
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majority of citations found were single case reports or case series. Another problem is that the clinical significance of IEDs is mainly discussed in neurology (Gorji and Speckmann 2009), but often unrecognised and rarely studied in psychiatry (Boutros 2009). Therefore, clinicians caring for psychiatric patients need to develop the necessary skills to be able to interpret results from advancing neurodiagnostic technologies (Boutros et al. 2013a, b). Psychiatric clinicians need to be more familiar with electroencephalography, its advantages as well as its limitations. More research is needed in this field to better define indications, adequate EEG workups, best AEDs to be used and optimal durations of treatment (Boutros et al. 2014). Multimodal EEG approaches, including resting and long-term recordings, and simultaneous video-EEG-recordings should be considered during the diagnostic workup of PD patients (Adamaszek et al. 2011). With recent developments in the investigation of altered synchronous neuronal activities (such as the combination of EEG/fMRI or MEG and coherence or microstate analysis), there are a couple of promising techniques emerging which may be helpful to better understand the underlying neurophysiologic mechanisms of PD in the future (Ray et al. 2007; Jacobs et al. 2009; Adamaszek et al. 2011).
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